AIMC Topic: Middle Aged

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Leveraging natural language processing to enhance feedback-informed group therapy: A proof of concept.

Psychotherapy (Chicago, Ill.)
Group therapy has evolved as a powerful therapeutic approach, facilitating mutual support, interpersonal learning, and personal growth among members. However, the complexity of studying communication dynamics, emotional expressions, and group interac...

Diagnostic Value of Median Nerve Cross-sectional Area Measured by Ultrasonography for the Severity of Carpal Tunnel Syndrome: A Machine Learning-Based Approach.

American journal of physical medicine & rehabilitation
OBJECTIVE: This study was conducted to evaluate the diagnostic performance and to establish cutoff values of median nerve cross-sectional area for classifying the severity of carpal tunnel syndrome.

Automated contouring for breast cancer radiotherapy in the isocentric lateral decubitus position: a neural network-based solution for enhanced precision and efficiency.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
BACKGROUND: Adjuvant radiotherapy is essential for reducing local recurrence and improving survival in breast cancer patients, but it carries a risk of ischemic cardiac toxicity, which increases with heart exposure. The isocentric lateral decubitus p...

A machine learning model using clinical notes to estimate PHQ-9 symptom severity scores in depressed patients.

Journal of affective disorders
BACKGROUND: Lack of widespread use of the Patient Health Questionnaire 9-item (PHQ-9) in clinical practice inhibits measurement of treatment follow-up for patients with major depressive disorder (MDD). This study developed, validated and applied a ma...

Machine Learning-Based CT Radiomics Model to Predict the Risk of Hip Fragility Fracture.

Academic radiology
RATIONALE AND OBJECTIVES: This research aimed to develop a combined model based on proximal femur attenuation values and radiomics features at routine CT to predict hip fragility fracture using machine learning methods.

Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study.

The Lancet. Digital health
BACKGROUND: Emerging evidence suggests that artificial intelligence (AI) can increase cancer detection in mammography screening while reducing screen-reading workload, but further understanding of the clinical impact is needed.

Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.

Journal of the American Heart Association
BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often goes undiagnosed in part because of low suspicion and screening tools not being easily accessible such as echocardiography. A new readily available scre...

Clinician Experiences With Ambient Scribe Technology to Assist With Documentation Burden and Efficiency.

JAMA network open
IMPORTANCE: Timely evaluation of ambient scribing technology is warranted to assess whether this technology can lessen the burden of clinical documentation on clinicians.

Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning.

BMC medical informatics and decision making
BACKGROUND: Respiratory diseases and Cardiovascular Diseases (CVD) often coexist, with airflow obstruction (AO) severity closely linked to CVD incidence and mortality. As both conditions rise, early identification and intervention in risk populations...